Exploiting 3D Variational Autoencoders For Interactive Vehicle Design

Sneha Saha, Leandro Minku, Xin Yao, Bernard Sendhoff, Stefan Menzel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In automotive digital development, 3D prototype creation is a team effort of designers and engineers, each contributing with ideas and technical evaluations through means of computer simulations. To support the team in the 3D design ideation and exploration task, we propose an interactive design system for assisted design explorations and faster performance estimations. We utilize the advantage of deep learning-based autoencoders to create a low-dimensional latent manifold of 3D designs, which is utilized within an interactive user interface to guide and strengthen the decision-making process.
Original languageEnglish
Title of host publicationINTERNATIONAL DESIGN CONFERENCE – DESIGN 2022
Publication statusAccepted/In press - 1 Feb 2022

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